What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI agents discover and use tools natively. Instead of writing API integration code, you simply point your MCP-compatible client at our server and the AI automatically discovers all available tools, their parameters, and how to call them.

Our MCP server exposes the same capabilities as the REST API: resume optimization, job matching, and resume parsing. The difference is that MCP clients like Claude Code, Claude Desktop, Cursor, Windsurf, and others can connect with zero integration code.

Supported Clients

Quick Start

To connect your MCP client, you need two things:

1. A paid subscription with an API key from your Account Settings
2. An MCP-compatible client (see supported clients above)

Server URL

Transport

Streamable HTTP (the standard MCP HTTP transport)

Client Setup

Claude Code

Add the server to your MCP configuration:

Claude Desktop / Cursor / Windsurf

Add this to your MCP settings file:

{
  "mcpServers": {
    "resume-optimizer": {
      "type": "streamable-http",
      "url": "https://resumeoptimizerpro.com/api/mcp"
    }
  }
}

Custom Agents (MCP SDK)

Connect programmatically using any MCP client SDK:

// C# example using ModelContextProtocol NuGet package
var client = await McpClientFactory.CreateAsync(
    new StreamableHttpClientTransport("https://resumeoptimizerpro.com/api/mcp"));

var tools = await client.ListToolsAsync();
var result = await client.CallToolAsync("parse_resume", new Dictionary<string, object>
{
    ["apiKey"] = "your-api-key",
    ["resumeText"] = "John Doe, Software Engineer..."
});

Authentication

Every tool call requires your API key as the apiKey parameter. This is the same API key used for the REST API. You can find or generate your API key in your Account Settings.

Available Tools

The MCP server exposes three tools. Each tool accepts the same parameters as the corresponding REST API endpoint.

optimize_resume

Takes a resume and returns a fully optimized, ATS-compatible version. Optionally targets a specific job posting when autoOptimize is enabled.

Parameters

Response

Returns the same response as the REST API optimize endpoint, including:

• OptimizedResumeAsBase64String — The optimized resume as a .docx file (base64 encoded)
• CoverLetterAsBase64String — The cover letter as a .docx file (if requested)
• CandidateName — The candidate's name
• OptimizedResumeAsJson — The structured resume data
• StatusCode, Message, CreditsRemaining

match_resume

Evaluates a resume's alignment with a job posting and identifies strong matches, partial matches, gaps, required skills, and provides a matching score.

Parameters

Response

Returns the same response as the REST API match endpoint, including:

• AdditionalSkillsNeededForJob — Skills missing from the resume
• SkillsAlreadyInResume — Skills already present
• JobMatchAnalysis.MatchingScore — Score from 0 to 100
• JobMatchAnalysis.StrongMatches, PartialMatches, Gaps
• JobMatchAnalysis.ResultsSummary — Brief summary of results
• JobMatchAnalysis.InterviewQuestions — Sample Q&A (if requested)
• StatusCode, Message, CreditsRemaining

parse_resume

Takes a resume and returns its unmodified parsed data as structured JSON, including a resume analysis that evaluates adherence to best practices.

Parameters

Response

Returns the same response as the REST API parse endpoint, including:

• ParsedResumeAsJson — Structured resume data (contact info, work history, education, skills, certifications)
• StatusCode, Message, CreditsRemaining

Example Workflow

Here is a typical workflow for optimizing a resume for a specific job using an AI agent:

1. Match first — Use match_resume to analyze the resume against the job description and identify skill gaps.
2. Optimize — Use optimize_resume with the identified gaps passed as skillsToAdd and autoOptimize set to true.
3. Review — The AI agent can present the results to the user for review, highlighting changes made and the new matching score.

With MCP, the AI agent handles all of this automatically. Simply ask: "Optimize my resume for this job posting" and the agent will execute the right sequence of tool calls.

Credits

Each MCP tool call consumes the same credits as the equivalent REST API call. Credit usage is identical regardless of whether you use MCP or the REST API. Your remaining credits are included in every response.

Rate Limits

The same rate limits apply to MCP and REST API requests. If your application requires higher limits, please contact us.